confIntProportion: Compute confidence interval for a binomial proportion via...
In biostatUZH: Misc Tools of the Department of Biostatistics, EBPI, University of Zurich

Description Usage Arguments Value Author(s) References See Also Examples

Compute a confidence interval for a binomial proportion using several asymptotic and exact methods. The individual methods are also available as separate functions wald, wilson, agresti, jeffreys, and clopperPearson.

1	confIntProportion(x, n, conf.level = 0.95)

`x`	Number of successes.
`n`	Total number of trials.
`conf.level`	Confidence level for confidence interval.

A list with the entries:

`p`	Estimated proportion.
`CIs`	Dataframe containing the estimated confidence intervals.

Kaspar Rufibach and Leonhard Held

All the intervals provided in these functions are compared in:

Brown, L.D., Cai, T.T., DasGupta, A. (2001). Interval Estimation for a Binomial Proportion. Statistical Science, 16(2), 101–133.

Functions for some of the intervals provided here are available in Hmisc (see the examples).

## Calculate confidence bounds for a binomial parameter by different methods. 
x <- 50
n <- 100
ci <- confIntProportion(x, n)$CIs
ci

plot(0, 0, type = 'n', ylim = c(0, 7), xlim = c(0, 1), xlab = 'p', 
    ylab = '', yaxt = 'n')
lines(ci[1, 2:3], c(1, 1))
lines(ci[2, 2:3], c(2, 2))
lines(ci[3, 2:3], c(3, 3))
lines(ci[4, 2:3], c(4, 4))
lines(ci[5, 2:3], c(5, 5))
text(0.5, 0.85, 'wald')
text(0.5, 1.85, 'wilson')
text(0.5, 2.85, 'agresti')
text(0.5, 3.85, 'jeffreys')
text(0.5, 4.85, 'clopper')

## compare intervals to those received by the function binconf in Hmisc:
if (require("Hmisc")) {
    binconf(x, n, method = "asymptotic")   # Wald
    binconf(x, n, method = "wilson")       # Wilson
    binconf(x, n, method = "exact")        # Clopper-Pearson
}